H.264s extensive use of context-based adaptive binary arithmetic or variable length coding makes streams highly
susceptible to channel errors, a common occurrence over networks such as those used by mobile devices. Even a single
bit error will cause a decoder to discard all stream data up to the next fixed length resynchronisation point, the worst
scenario is that an entire slice is lost. In cases where retransmission and forward error concealment are not possible, a
decoder should conceal any erroneous data in order to minimise the impact on the viewer. Stream errors can often be
spotted early in the decode cycle of a macroblock which if aborted can provide unused processor cycles, these can
instead be used to conceal errors at minimal cost, even as part of a real time system. This paper demonstrates a technique
that utilises Sobel convolution kernels to quickly analyse the neighbourhood surrounding erroneous macroblocks before
performing a weighted multi-directional interpolation. This generates significantly improved statistical (PSNR) and
visual (IEEE structural similarity) results when compared to the commonly used weighted pixel value averaging.
Furthermore it is also computationally scalable, both during analysis and concealment, achieving maximum performance
from the spare processing power available.